Fire Hotspots Detection System on CCTV Videos Using You Only Look Once (YOLO) Method and Tiny YOLO Model for High Buildings Evacuation

Fire is one of the disasters in high buildings that often leads to many material losses and casualties. In general, material and nonmaterial loss of fire incidents can be minimized by solving it quickly. To minimize the extent of the fire area, we need technology to detect the existence of fire hots...

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Bibliographic Details
Published in2019 2nd International Conference of Computer and Informatics Engineering (IC2IE) pp. 87 - 92
Main Authors Lestari, Dewi Putrie, Kosasih, Rifki, Handhika, Tri, Murni, Sari, Ilmiyati, Fahrurozi, Achmad
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.09.2019
Subjects
Buildings
CCTV videos
Computational modeling
evacuation
fire hotspots
Informatics
Testing
Training
Training data
Videos
You Only Look Once (YOLO)
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Summary:Fire is one of the disasters in high buildings that often leads to many material losses and casualties. In general, material and nonmaterial loss of fire incidents can be minimized by solving it quickly. To minimize the extent of the fire area, we need technology to detect the existence of fire hotspots before fires become widely. At first, the fire early detection system uses a sensor, but many sensors cannot stand fire. Therefore, another method needed that can monitor an area in the building from a distance. In this study, CCTV cameras were used to see whether there was a fire hotspot or not. As additional technology, we use artificial intelligence to analyze the results of CCTV. We propose the You Only Look Once (YOLO) method to detect fire hotspots on CCTV videos. In this study, the YOLO method can recognize fire hotspots with an average value of accuracy is 90%.
DOI:10.1109/IC2IE47452.2019.8940842